list_subscriptionsList the caller's active subscriptions. Returns id, type, params, created_at, last_fired_at, fire_count for each. Use this to review what you're monitoring before adding more or to find an id to cancel.
| Name | Required | Description | Default |
|---|---|---|---|
| include_inactive | No | Include cancelled subscriptions in the response (default false). |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and destructiveHint=false. The description adds value by specifying the return fields and scoping to the caller's subscriptions, which gives the agent a fuller picture of the behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loads the purpose, and each sentence adds distinct information: what it returns and when to use it. No word wasted.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple list tool with one optional parameter and good annotations, the description provides the purpose, return field list, and usage context. This is sufficient for an agent to select and invoke the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% for the sole parameter include_inactive, so the schema already conveys its meaning. The tool description does not need to add more, hence baseline score of 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'List the caller's active subscriptions' with a specific verb and resource. It specifies the returned fields and distinguishes itself from mutation siblings like subscribe and unsubscribe.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
It provides explicit usage guidance: 'Use this to review what you're monitoring before adding more or to find an id to cancel.' This gives clear when-to-use scenarios, though it doesn't explicitly name the alternative subscribe tool, so it's strong but not perfect.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
The tool set mixes multiple domains (Postmark email, Pipeworx data queries, Polymarket betting, memory utilities) with several overlapping tools. ask_pipeworx and ask_pipeworx_beta are essentially identical, send/send_batch and bounces/bounce are similar, and multiple polymarket analysis tools (polymarket_arbitrage, polymarket_edges, polymarket_edge_tracker) could be confused. Despite detailed descriptions, the sheer number of query and analysis tools increases the chance of misselection.
All tool names use lowercase_with_underscores, so the casing is consistent. However, there is no uniform verb_noun pattern: some start with verbs (ask, send, bounce, resolve, validate), while others are noun phrases (server, bounces, recent_alerts, entity_profile). This mixed semantic structure makes it less predictable, but the names are still readable.
41 tools is far above the typical well-scoped range of 3-15. The server combines multiple unrelated domains—email, data lookup, prediction markets, memory, and subscriptions—resulting in a heavyweight and unfocused surface. Most of the tools would be better split into separate, purpose-specific servers.
For a server named Postmark, the email side is incomplete: there is no update server configuration, message stream management, or inbound email handling. The Pipeworx data tools provide good read coverage but lack write/management operations for entities. The inclusion of unrelated tools makes the surface feel arbitrary rather than complete for any single domain.